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OHI-Northeast | OHI Science | Citation policy

Summary

This script creates the Iconic Species status data layer for use in the Sense of Place: Iconic Species subgoal. A list of 33 iconic species was created following input from multiple folks in the region. The Iconic Species status layer calculates the conservation status score (0 = extinct, 1 = least concern) for each of the iconic species.


Data Source

We use NatureServe and IUCN conservation status (aka extinction risk) information.


Load Data

Load the list of our iconic species. This list was created manually through consultation with folks in the region about iconic Northeast species.

Species range (i.e. where the species is found) and conservation status information comes from a layer in the Biodiversity - Species subgoal. The spp_status_scores.csv contains information about each species in our region, their conservation status and the associated score between 0 and 1 (where 0 is low extinction risk and 1 is extinct). spp_rgns.csv contains info on where each species is found within the Northeast. Both of these files are created in the prep/bio/spp folder and these two .csv’s live in the ne-scores repository.

##  [1] "alewife"                    "american lobster"          
##  [3] "american shad"              "arctic tern"               
##  [5] "atlantic bluefin tuna"      "atlantic cod"              
##  [7] "atlantic herring"           "atlantic puffin"           
##  [9] "atlantic sturgeon"          "bald eagle"                
## [11] "bottlenose dolphin"         "common tern"               
## [13] "fin whale"                  "haddock"                   
## [15] "horseshoe crab"             "humpback whale"            
## [17] "least tern"                 "minke whale"               
## [19] "north atlantic right whale" "osprey"                    
## [21] "roseate tern"               "sandbar shark"             
## [23] "sea scallop"                "sperm whale"               
## [25] "striped bass"               "great white shark"
## [1] "american oyster"   "blue crab"         "bay scallop"      
## [4] "atlantic surfclam" "soft shell clam"   "northern quahog"  
## [7] "atlantic salmon"   "piping plover"

Filter dataset just for iconic species

Did we get all 33 species?

##  [1] "alewife"                    "american lobster"          
##  [3] "american shad"              "arctic tern"               
##  [5] "atlantic bluefin tuna"      "atlantic cod"              
##  [7] "atlantic herring"           "atlantic puffin"           
##  [9] "atlantic sturgeon"          "bald eagle"                
## [11] "bottlenose dolphin"         "common tern"               
## [13] "fin whale"                  "haddock"                   
## [15] "horseshoe crab"             "humpback whale"            
## [17] "least tern"                 "minke whale"               
## [19] "north atlantic right whale" "osprey"                    
## [21] "roseate tern"               "sandbar shark"             
## [23] "sperm whale"                "striped bass"              
## [25] "great white shark"

We only have 25 species in the spp_status_scores data. What are we missing?

## [1] "american oyster"   "blue crab"         "bay scallop"      
## [4] "sea scallop"       "atlantic surfclam" "soft shell clam"  
## [7] "northern quahog"   "atlantic salmon"   "piping plover"

Most of the species we are missing are a harvested (commercially fished) species, except for Piping plover. I’m going to see if Nature Serve has this species.

#install.packages("natserv")
library(natserv)
options(NatureServeKey = Sys.getenv("NatureServeKey"))

id <- ns_search(x = "Charadrius melodus")$globalSpeciesUid
id_dat  <- ns_data(uid = id)
#state level conservation status
state <- id_dat[[1]]$conservationStatus$natureserve$nationalStatuses$US$subnationalStatuses
#us rank for region 12
pp_us <- id_dat[[1]]$conservationStatus$natureserve$nationalStatuses$US$rank

  #create an empty dataframe to cycle through each state
  out <- data.frame(state = NA,
                    rank = NA)

for(j in 1:length(state)){
    
    ST <- state[[j]]$subnationCode
  
    if(ST %in% c("CT", "NY", "MA", "ME", "RI", "NH")){
      state_rank <- state[[j]]$rank
      
      df <- data.frame(state = ST, rank = state_rank, stringsAsFactors = F)
    }else{
      df <- data.frame(state = NA, rank = NA, stringsAsFactors = F)
    }
    out <- rbind(out, df) %>%
      filter(!is.na(state))
}
  
  #add in the US rank
  out <- out %>%
    add_row(state = "USA", rank = pp_us)
  
  #read in natureserve scores for the status
ns_scores <- read_csv("~/github/ne-prep/prep/bio/spp/data/natserv_status_scores.csv") %>% select(-X1)

pp <- out %>%
  left_join(ns_scores, by = c("rank" = "status")) %>%
  left_join(rgn_data, by = c("state" = "state_abv")) %>%
  mutate(common = "piping plover",
         sciname = "Charadrius melodus",
         year = 2017,
         status_scale = state,
         score = 1-score) %>%
  select(common, sciname, status = rank, status_scale, rgn_name, rgn_id, score, year) %>%
  mutate(rgn_name = ifelse(status_scale == "USA", "Northeast", rgn_name),
         rgn_id = ifelse(status_scale == "USA", 12, rgn_id))

We will use our stock scores for these species where available. The nmfs_stock_scores.csv dataset was created in the Seafood Provision - Wild-Caught Fisheries subgoal data prep.

## [1] "Atlantic salmon"   "Atlantic surfclam" "Sea scallop"

Only three of the species have stock assessments from NMFS that we can use as scores. So looks like we are missing american oyster, blue crab, bay scallop, soft shell clam, and quahog.

Find where these species exist

We don’t care about how big or small the species range map is, if a species exists within an OHI region we will count it there.

## # A tibble: 11 x 3
##    rgn_id common      sciname                 
##     <dbl> <chr>       <chr>                   
##  1     12 sea scallop placopecten magellanicus
##  2      1 sea scallop placopecten magellanicus
##  3      2 sea scallop placopecten magellanicus
##  4      3 sea scallop placopecten magellanicus
##  5      4 sea scallop placopecten magellanicus
##  6      6 sea scallop placopecten magellanicus
##  7      7 sea scallop placopecten magellanicus
##  8      8 sea scallop placopecten magellanicus
##  9      9 sea scallop placopecten magellanicus
## 10     10 sea scallop placopecten magellanicus
## 11     11 sea scallop placopecten magellanicus

We only have sea scallop identified to regions within the Northeast. That means we are missing salmon and surfclam. For now let’s assume they are everywhere. Combine rgn_areas with the scores

Correct species

Some species are not showing up in certain regions even though they are listed by the state in those areas. This could be due to the fact that species distribution models are not accurate enough to be captured in smaller regions like Connecticut or Long Island Sound. To account for this, we use a dataset provided by Emily Shumchenia that lists species in the portal and whether or not they are listed by state.

Filter just for iconic species

## [1] "american oyster"    "blue crab"          "horseshoe crab"    
## [4] "bay scallop"        "bald eagle"         "bottlenose dolphin"
## [7] "soft shell clam"

Find states where these species are listed

Combine this with the data we already have.

For species that are listed differently between Emily’s data and Natureserve, we defer to Emily. The following is listed on Natureserves website and states that their updates are latent. > U.S. & Canada State/Province Status Due to latency between updates made in state, provincial or other NatureServe Network databases and when they appear on NatureServe Explorer, for state or provincial information you may wish to contact the data steward in your jurisdiction to obtain the most current data. Please refer to our Distribution Data Sources to find contact information for your jurisdiction.

How many of our iconic species do we have?

Look at where these species are found.

For those species in a region where they are found but without a state status, use the USA designated one. Here I also add Great White Shark to each of the regions in the Northeast. We only have scores for USA/IUCN but need to assign it to all the regions. I’m also adding Horseshoe Crab to Maine (https://dmc.umaine.edu/2015/02/05/horseshoe-crab-report-local-effort/)

Use USA designated status for region 12, the whole Northeast

Format for toolbox

We need to add all years even though we dont have any information that tells us status changes. So these scores will all be the same over the entire time period

We only assess Sense of Place for coastal regions so we need to set offshore replace all offshore region scores with NA.

Results

Table

Since we see no changes over time let’s just look at 2017 in table form

Heatmap

Need to create a dataframe for background of heat map so that missing values are not blank. Dataframe below has every iconic species in every region

Create dataframe that matches scores with status

with status label

Heatmap with scores

Heatmap with status level